def test_isotropic_ps_slope(chunk, N=512, dL=1.0, amp=1e1, s=-3.0):
"""Test the spectral slope of isotropic power spectrum."""
theta = synthetic_field_xr(
N,
dL,
amp,
s,
other_dim_sizes=[10],
dim_order=True,
)
if chunk:
theta = theta.chunk({"d0": 2})
iso_ps = xrft.isotropic_power_spectrum(
theta, dim=["y", "x"], detrend="constant", density=True
).mean("d0")
npt.assert_almost_equal(np.ma.masked_invalid(iso_ps).mask.sum(), 0.0)
y_fit, a, b = xrft.fit_loglog(iso_ps.freq_r.values[4:], iso_ps.values[4:])
npt.assert_allclose(a, s, atol=0.1)
iso_ps_sequal = np.zeros((len(theta.d0), int(N / 4)))
for i in range(len(theta.d0)):
iso_ps_sequal[i] = xrft.isotropic_power_spectrum(
theta.isel(d0=i), detrend="constant", density=True
)
npt.assert_almost_equal(iso_ps.values, iso_ps_sequal.mean(axis=0))
def test_isotropic_ps_slope(N=512, dL=1., amp=1e1, s=-3.):
"""Test the spectral slope of isotropic power spectrum."""
theta = xr.DataArray(_synthetic_field(N, dL, amp, s),
dims=['y', 'x'],
coords={'y':range(N), 'x':range(N)})
iso_ps = xrft.isotropic_powerspectrum(theta, detrend='constant',
density=True)
npt.assert_almost_equal(np.ma.masked_invalid(iso_ps[1:]).mask.sum(), 0.)
y_fit, a, b = xrft.fit_loglog(iso_ps.freq_r.values[4:],
iso_ps.values[4:])
npt.assert_allclose(a, s, atol=.1)
def test_isotropic_ps_slope(N=512, dL=1., amp=1e1, s=-3.):
"""Test the spectral slope of isotropic power spectrum."""
theta = xr.DataArray(synthetic_field(N, dL, amp, s),
dims=['y', 'x'],
coords={'y':range(N), 'x':range(N)})
iso_ps = xrft.isotropic_power_spectrum(theta, detrend='constant',
density=True)
npt.assert_almost_equal(np.ma.masked_invalid(iso_ps[1:]).mask.sum(), 0.)
y_fit, a, b = xrft.fit_loglog(iso_ps.freq_r.values[4:],
iso_ps.values[4:])
npt.assert_allclose(a, s, atol=.1)